Discovery of Online Shopping Patterns Across Websites

Abstract

I n the online world, customers can easily navigate to different online stores to make purchases. The products purchased on one site are often associated with product purchases on other sites (e.g., a hotel reservation on one site and a car rental on another site). Whereas market basket analysis is often used to discover associations among products for brick-and-mortar stores, it is rarely applied in the online setting where consumers navigate among different online stores to buy products. We define online shopping patterns and develop two novel methods to perform market basket analysis across websites. While this research is motivated by online shopping applications, our contribution is mainly methodological. The two methods we develop in this paper can not only be used to identify various online shopping patterns across sites and products but can also be applied to settings where patterns exist across different dimensions. Experiments on both synthetic data and real online shopping data demonstrate the effectiveness of our methods.

Bibliometric analysis of carsharing and car rental research in the field of urban transportation and tourism transportation

“…Finally, the fifth cluster (in yellow) reflected a few mixed papers, but holistically they examined travel behavior, transportation policy, sustainable transport, energy consumption and car ownership under mobility as a service (Becker et al, 2018;Dowling & Kent, 2015;Yinghui et al, 2011). Some articles focused on car ownership, consumer awareness and carsharing intention as well (Burlando et al, 2019;Ikezoe et al, 2020).…”

“…The second cluster (in yellow, bottom right) consists of articles on the e-commerce practices of car rental businesses in the online world. Scientists have focused on online travel transactions, online purchasing and how it affects purchase decisions (Marcus & Anderson, 2006;Venkateshwara & Smith, 2006;Yinghui et al, 2011).…”

Discovery Shopping eCommerce untuk Meningkatkan Pengalaman Pelanggan pada UMKM Produk Tanaman Herbal, Sayuran, dan Alat Berkebun

“…DSC mengacu pada kebiasaan seseorang melihat-lihat sesuatu di suatu toko, menjelajahi suatu etalase tanpa ada intensi untuk melakukan transaksi, atau yang lebih dikenal dengan window shopping. Dalam hal ini, pengguna diberi kebebasan untuk mencari tahu dan menemukan informasi sebanyak-banyaknya terkait beberapa produk sampai ditemukan sebuah produk yang menarik perhatiannya [8] . DSC ini menjadi jalan bagi salah satu tujuan dari eCommerce itu sendiri, yaitu penemuan produk yang membantu pelanggan membuat keputusan untuk melakukan transaksi jual beli.…”

Predicting customer purchase behavior in the e-commerce context

“…Mobasher et al [15] use frequent item mining techniques to discover sequential patterns that are used to generate recommendations. Yang et al [31] define online shopping patterns and develop methods to perform market basket analysis across websites. Discrete choice models may be employed to analyze customer preferences, which play an important role in purchasing decisions.…”

“…Research efforts from the marketing and customer relationship management (CRM) perspectives have made major strides in predicting customer purchase behavior. For example, market basket analysis [29,31] examines groups of items purchased in supermarkets or other outlets to identify purchase patterns, and discrete choice models [16,30] predict which products a specific customer is likely to select from a candidate product set. Certain studies abstract the prediction of purchase behavior into a classification task [7,10] that requires customers' demographic features, such as age, gender, education and occupation.…”